Opportunity Information: Apply for RFA RM 27 013
Apply for RFA RM 27 013
- The National Institutes of Health in the health sector is offering a public funding opportunity titled "Model-to-Clinic (M2C) for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (UG3/UH3, Clinical Trial Optional)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.310.
- This funding opportunity was created on 2026-06-30.
- Applicants must submit their applications by 2026-10-19. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The number of recipients for this funding is limited to 8 candidate(s).
- Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.
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Opportunity Summary:
The NIH funding opportunity RFA-RM-27-013, titled "Model-to-Clinic (M2C) for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (UG3/UH3, Clinical Trial Optional)," is a cooperative agreement designed to push AI-enabled clinical decision support tools out of the prototype stage and into real clinical use. The larger PRIMED-AI Program is focused on precision medicine approaches that treat clinical imaging as the central signal and then strengthen it by combining it with other health data types (multimodal data). The practical aim is to produce decision support tools that are not only innovative, but also reliable, cost-effective, and sustainable in everyday healthcare settings, so that AI can be adopted inside clinical workflows rather than remaining a research-only capability.
A key emphasis of this opportunity is "model-to-clinic" translation. Projects should move beyond developing or benchmarking models in isolation and instead advance image-centered, multimodal AI systems toward clinical application, where they can address clear unmet needs. The tools envisioned here are clinical decision support (CDS) systems that integrate imaging (for example, radiology, pathology, or other clinical imaging modalities) with additional data streams such as electronic health record data, laboratory values, vital signs, clinical notes, genomics, or other relevant patient-level information. The opportunity frames these tools as Software as a Medical Device (SaMD), meaning applicants should be thinking in terms of real-world clinical deployment considerations like performance consistency, usability, workflow fit, and the kinds of evidence expected when software is intended to inform clinical decisions.
The NOFO also signals the kinds of outcomes NIH expects to see. Proposed projects should have strong potential to demonstrate measurable, positive impact, either by improving patient outcomes and care quality or by improving healthcare processes (for example, reducing time to diagnosis, triaging more accurately, lowering unnecessary testing, improving treatment selection, or making care delivery more efficient). In other words, success is not just a better AUC on a held-out dataset, but a credible path to clinical value where the tool can be used by clinicians and can change decisions or operations in a beneficial way.
Mechanistically, this is a UG3/UH3 phased cooperative agreement. While the NOFO text provided does not detail the phase-specific milestones, UG3/UH3 awards generally use an initial phase to complete key planning, validation, and readiness activities, followed by a second phase focused on fuller execution and translation once predefined milestones are met. The "clinical trial optional" designation means applicants may propose projects that do or do not include a clinical trial component, depending on what is necessary to responsibly evaluate and advance the CDS tool toward use.
Eligibility is broad and intentionally inclusive. A wide range of U.S. entities can apply, including state, county, and local governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; nonprofit organizations (both 501(c)(3) and non-501(c)(3), excluding higher education where specified); for-profit organizations other than small businesses; and small businesses. Tribal governments and tribal organizations are also eligible, as are public housing authorities/Indian housing authorities. Importantly, the opportunity explicitly allows international participation: non-U.S. entities (foreign organizations) may apply, non-U.S. components of U.S. organizations are eligible, and foreign components are allowed consistent with NIH policy, which can be especially relevant for multinational data resources, cross-site validation, and diverse population evaluation.
The award is administered by the National Institutes of Health under CFDA 93.310, categorized under health, and uses a cooperative agreement funding instrument, which typically implies substantial NIH programmatic involvement compared with standard grants. NIH anticipates making about eight awards under this NOFO. The original closing date listed is 2026-10-19, and the opportunity was created on 2026-06-30. While an award ceiling is not specified in the provided text, applicants should expect the cooperative nature and the UG3/UH3 structure to require clear milestones, deliverables, and a convincing plan for progressing an AI-driven, image-centered, multimodal CDS product toward clinical integration and impact.
Frequently Asked Questions (FAQ) - NIH RFA-RM-27-013 (PRIMED-AI) UG3/UH3
1) What is this funding opportunity?
This NIH funding opportunity is RFA-RM-27-013, titled "Model-to-Clinic (M2C) for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (UG3/UH3, Clinical Trial Optional)." It supports projects that move AI-enabled clinical decision support tools from prototype-stage research into real clinical use, with clinical imaging as the central signal combined with other patient-level data (multimodal data).
2) What is the main goal of PRIMED-AI as described here?
The larger PRIMED-AI Program emphasizes precision medicine approaches where clinical imaging (such as radiology or pathology) is strengthened by integrating it with multimodal health data. The practical goal is to produce decision support tools that are innovative but also reliable, cost-effective, and sustainable in everyday clinical settings, so they can be adopted inside clinical workflows rather than staying research-only.
3) What does "Model-to-Clinic" translation mean in this NOFO?
"Model-to-clinic" translation means projects should go beyond developing or benchmarking models in isolation. Applicants are expected to advance image-centered, multimodal AI systems toward clinical application where they can address clear unmet clinical needs and demonstrate a credible path to real-world clinical value.
4) What kinds of tools are envisioned (what is a CDS system in this context)?
The NOFO envisions clinical decision support (CDS) systems that integrate imaging with additional data streams such as electronic health record data, laboratory values, vital signs, clinical notes, genomics, or other relevant patient-level information. The expectation is that these tools support clinical decisions or healthcare operations in meaningful ways.
5) Is imaging required, and how is it used?
Imaging is treated as the central signal in this opportunity. The concept is image-centered AI that is strengthened by multimodal data integration. Examples of imaging mentioned include radiology, pathology, and other clinical imaging modalities.
6) What does "multimodal data" mean here?
Multimodal data refers to patient-level information beyond imaging that can be combined with images to improve precision medicine decision support. Examples provided include EHR data, lab values, vital signs, clinical notes, genomics, and other relevant data types.
7) What does it mean that these tools are considered Software as a Medical Device (SaMD)?
The NOFO frames the envisioned CDS tools as Software as a Medical Device (SaMD). This signals that applicants should plan for real-world clinical deployment considerations, including performance consistency, usability, workflow fit, and the kind of evidence expected when software is intended to inform clinical decisions in practice.
8) What kinds of outcomes does NIH expect projects to demonstrate?
NIH expects measurable, positive impact. This can include improving patient outcomes and care quality, or improving healthcare processes. Examples mentioned include reducing time to diagnosis, improving triage accuracy, lowering unnecessary testing, improving treatment selection, or increasing efficiency in care delivery. Success is described as more than better metrics on a held-out dataset; it requires a credible path to clinical value and practical use by clinicians.
9) Does this opportunity require a clinical trial?
No. The NOFO is labeled "Clinical Trial Optional," meaning applicants may propose projects that include a clinical trial component or projects that do not, depending on what is necessary to responsibly evaluate and advance the CDS tool toward clinical use.
10) What is the funding mechanism and why does it matter?
This opportunity uses a cooperative agreement funding instrument. Compared with standard grants, cooperative agreements typically involve substantial NIH programmatic involvement. Applicants should anticipate the need for clear milestones and deliverables aligned with advancing an AI-driven, image-centered multimodal CDS tool toward real clinical integration and impact.
11) What is a UG3/UH3 phased cooperative agreement?
The award mechanism is UG3/UH3, which is a phased structure. While the provided text does not list the specific phase-by-phase milestones, UG3/UH3 awards generally include an initial phase focused on planning, validation, and readiness activities, followed by a second phase focused on fuller execution and translation once predefined milestones are successfully met.
12) Who is eligible to apply?
Eligibility is broad. Eligible applicants include U.S. state, county, and local governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; nonprofit organizations (including 501(c)(3) and non-501(c)(3), excluding higher education where specified); for-profit organizations other than small businesses; small businesses; tribal governments and tribal organizations; and public housing authorities/Indian housing authorities.
13) Are international (non-U.S.) organizations eligible?
Yes. The opportunity explicitly allows international participation: non-U.S. entities (foreign organizations) may apply; non-U.S. components of U.S. organizations are eligible; and foreign components are allowed consistent with NIH policy. This may be relevant for multinational data resources, cross-site validation, and evaluation across diverse populations.
14) Which agency administers the award and what is the program category?
The award is administered by the National Institutes of Health (NIH). It is categorized under health and is associated with CFDA 93.310.
15) How many awards does NIH expect to make?
NIH anticipates making about eight awards under this NOFO.
16) What is the application deadline and when was the opportunity created?
The original closing date listed is 2026-10-19. The opportunity was created on 2026-06-30.
17) Is there a maximum award amount (ceiling) provided in the information here?
No award ceiling is specified in the provided text. Applicants should still plan for the cooperative nature of the mechanism and the UG3/UH3 structure, which typically require well-defined milestones, deliverables, and a strong plan for translation toward clinical integration.
18) What types of clinical impact are considered relevant for this program?
The NOFO highlights both clinical outcome improvements and process improvements. Relevant impacts include faster diagnosis, better triage, fewer unnecessary tests, improved treatment selection, and more efficient care delivery. The emphasis is on changes that can realistically occur in clinical workflows rather than improvements that only appear in retrospective model benchmarking.
19) What level of readiness is implied for proposed AI systems?
The opportunity is aimed at pushing tools out of the prototype stage and into real clinical use. That implies proposals should focus on readiness for deployment considerations such as consistent performance, usability, workflow fit, and practical evidence generation suitable for software that informs clinical decisions.
20) What is the core technical theme applicants should align with?
The core theme is image-centered AI for precision medicine that integrates imaging with multimodal data. Projects should be oriented toward clinical decision support and designed with translation to clinical environments in mind.
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